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Mufei Li
Mufei Li
Georgia Institute of Technology
Подтвержден адрес электронной почты в домене gatech.edu - Главная страница
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Процитировано
Процитировано
Год
Deep graph library: A graph-centric, highly-performant package for graph neural networks
M Wang, D Zheng, Z Ye, Q Gan, M Li, X Song, J Zhou, C Ma, L Yu, Y Gai, ...
arXiv preprint arXiv:1909.01315, 2019
13932019
Deep graph library: Towards efficient and scalable deep learning on graphs
M Wang, L Yu, D Zheng, Q Gan, Y Gai, Z Ye, M Li, J Zhou, Q Huang, C Ma, ...
ICLR workshop on representation learning on graphs and manifolds, 2019
8562019
Dgl-lifesci: An open-source toolkit for deep learning on graphs in life science
M Li, J Zhou, J Hu, W Fan, Y Zhang, Y Gu, G Karypis
ACS Omega, 2021
1762021
Drkg-drug repurposing knowledge graph for covid-19
VN Ioannidis, X Song, S Manchanda, M Li, X Pan, D Zheng, X Ning, ...
https://github.com/gnn4dr/DRKG, 2020
134*2020
A knowledge graph of clinical trials (CTKG)
Z Chen, B Peng, VN Ioannidis, M Li, G Karypis, X Ning
Scientific reports 12 (1), 4724, 2022
23*2022
Benchmarking Accuracy and Generalizability of Four Graph Neural Networks Using Large In Vitro ADME Datasets from Different Chemical Spaces
F Broccatelli, R Trager, M Reutlinger, G Karypis, M Li
Molecular Informatics (top 10 most-cited papers, 2022 - 2023), 2022
182022
De novo generation of dual-target ligands using adversarial training and reinforcement learning
F Lu, M Li, X Min, C Li, X Zeng
Briefings in Bioinformatics 22 (6), bbab333, 2021
152021
A statistical characterization of attentions in graph neural networks
M Li, H Zhang, X Shi, M Wang, Z Zhang
International Conference on Learning Representations (ICLR) 2019 Workshop on …, 2019
72019
Simple is Effective: The Roles of Graphs and Large Language Models in Knowledge-Graph-Based Retrieval-Augmented Generation
M Li*, S Miao*, P Li
International Conference on Learning Representations (*Equal contribution), 2024
52024
Graph Neural Networks in Life Sciences: Opportunities and Solutions
Z Wang, VN Ioannidis, H Rangwala, T Arai, R Brand, M Li, Y Nakayama
Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and …, 2022
52022
Opportunities and challenges of graph neural networks in electrical engineering
E Chien, M Li, A Aportela, K Ding, S Jia, S Maji, Z Zhao, J Duarte, V Fung, ...
Nature Reviews Electrical Engineering 1 (8), 529-546, 2024
42024
GraphMaker: Can Diffusion Models Generate Large Attributed Graphs?
M Li, E Kreačić, VK Potluru, P Li
Transactions on Machine Learning Research (TMLR), 2023
42023
Underestimated Privacy Risks for Minority Populations in Large Language Model Unlearning
R Wei, M Li, M Ghassemi, E Kreačić, Y Li, X Yue, B Li, VK Potluru, P Li, ...
arXiv preprint arXiv:2412.08559, 2024
2024
LayerDAG: A Layerwise Autoregressive Diffusion Model for Directed Acyclic Graph Generation
M Li, V Shitole, E Chien, C Man, Z Wang, S Sridharan, Y Zhang, T Krishna, ...
International Conference on Learning Representations (Spotlight), 2024
2024
KGExplainer: Towards Exploring Connected Subgraph Explanations for Knowledge Graph Completion
T Ma, W Tao, M Li, J Zhang, X Pan, J Lin, B Song, X Zeng
arXiv preprint arXiv:2404.03893, 2024
2024
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